The broad, long-term goal of this project is to develop, validate and study a large-scale dynamic neural network model of the human brain areas comprising the human mirror neuron system (MNS). This system is thought to enable an individual's understanding of the meaning of actions performed by others, and the potential imitation and learning of those actions, and recent studies implicate dysfunction of the MNS system in autism. However, little is known about the development and the plasticity of the MNS in infants and children, how these infants come to understand and acquire their first actions, and the degree of plasticity of the system in adults. To address these gaps, this project will use large-scale computer model simulations of the MNS to deepen our understanding of the basic neurobiological mechanisms and computational algorithms that underlie the development and plasticity of the MNS. By closely interacting with the Companion Projects, the model will integrate human and non-human primate data from various modalities including single cell recordings, scalp electroencephalogram (EEG), and behavior, and use these data to validate the model at various stages of development. Moreover, by using simulated developmental abnormalities reported in the literature, in a systematic fashion, we will assess the adequacy of the model to account for behavioral and EEG data reported in autism, and to increase our understanding of the functions and roles of the MNS in three fundamental abilities central to adaptive human functioning: 1) the ability to deploy actions strategically in service of goals, 2) the ability to infer the goals or actions of one's social partners, and 3) the ability to learn via imitation. In summary, this research proposes a series of experiments integrating behavioral, electrophysiological, and mathematical modeling methods to investigate the basic neurobiological mechanisms that underlie the emergence of the MNS in infants and its plasticity in adults.